• Medientyp: E-Artikel
  • Titel: Global Sensitivity Analysis with 2D Hydraulic Codes: Applied Protocol and Practical Tool
  • Beteiligte: Abily, Morgan [Verfasser:in]; Delestre, Olivier [Verfasser:in]; Gourbesville, Philippe [Verfasser:in]; Bertrand, Nathalie [Verfasser:in]; Duluc, Claire-Marie [Verfasser:in]; Richet, Yann [Verfasser:in]
  • Erschienen in: Journées de l'Hydraulique ; Vol. 36, n° 1, pp. 1-10
  • Sprache: Englisch
  • Schlagwörter: Sobol index ; 2D shallow water equation ; global sensitivity analysis ; flood hazard modelling ; Uncertainty ; article
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  • Beschreibung: Sensitivity analysis methods are useful tools as they allow robustness of model predictions to be checked and help to identify input parameters influences. Most commonly, Monte-Carlo approach is performed to propagate uncertainties. Various methods are then available to rank parameters regarding their impact on result variability (such as Sobol index). The whole process constitutes a Global Sensitivity Analysis (GSA). In practice, such type of approach is of a great interest, but is still at an exploratory level in applied studies relying on 2D Shallow Water Equations (SWE) codes. Indeed, a GSA approach implementation is challenging as it requires specific tools and deals with important computational capacity. The aim of this paper is to provide both a protocol and a tool to allow adaptable and ready-to use GSA for 2D hydraulic modelling applications. The coupling of an environment for parametric computation (Prométhée) and a code relying on 2D SWE (FullSWOF_ 2D), Promethée-FullSWOF_ 2D (P-FS) tool has been set up. P-FS tool allows launching directly numerous set of computation using R software. For a GSA study, the steps are : i) to identify the 2D hydraulic code input parameters of interest and to assign them a probability density function, ii) to propagate uncertainties within the model, and (iii) to rank the effects of input parameters variability on the output of interest variance. In this paper, a proof of concept of a GSA protocol implemented for 2D SWE models is presented. For our study case, 2000 simulations of a river flood event were run with uncertainties introduced through three parameters using P-FS tool. Tests were performed on regular computational mesh, spatially discretizing an urban area, using up to 17.9 million of computational points. P-FS tool has been installed on a cluster for computation. Method and P-FS tool successfully allow performing a Monte-Carlo approach within this data-base of 2000 simulations, to test convergence of the Monte- Carlo approach, and to produce maps of Sobol’ indices. The light is put on advantages and limits of the method and of developed P-FS tool.
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